The Science of Success

Our current approach to success is driven by the belief that predicting exceptional impact requires us to detect extraordinary ability. Despite the long-standing interest in the problem, even experts remain notoriously bad at predicting long-term impact. Success becomes suddenly predictable, however, if we see it not as an individual but a collective phenomenon: for something to be successful, it is not enough to be novel or appealing, but we all must agree that it is worthy of praise. If we accept the collective nature of success, its quantitative signatures can be uncovered from the many pieces of data around us using the tools of network and data science. In this course, we will focus on our ability to quantify and predict success, and how success emerges in various careers, from science to art and business. The course will draw material from a wide range of disciplines, from network science to social sciences and economics. This is a quantitative course, focusing on the quantifiable patterns that describe success. Hence students will be expected to read widely on the topic, as well as to perform a research project that quantifies success in an area of direct interest to them.

COURSE SCHEDULE

Week 1:

May 2, Tuesday: Introduction; Distinguishing performance from success

The First Law: Success is not about you, it’s about us.

May 3, Wednesday: The Second Law: Performance drives success.

May 5, Friday: The Third Law: Performance is bounded.

Week 2:

May 8, Monday: The Fourth Law: Success is unbounded.

May 10, Wednesday: The Fifth Law: Success breeds success.

May 12, Thursday: Preliminary Project Presentations

Week 3:

May 15, Monday: The Sixth Law: Quality multiplied by previous success determines success & The Seventh Law: Success can occur at any time.

May 16, Tuesday: The Ninth Law: High performing teams require equality, but the most successful teams require a leader. The Tenth Law: Credit is based on perception not performance.

May 17, Wednesday: Network determinants of success

Week 4:

May 31, Wednesday: Final Project Presentation

10 min/max 10 slides

Reading: The reading material will be handed out at the beginning of the course.

Learning Outcomes:

By successfully absolving the course the students will be able to:

- Recognize the relationship between performance and success;

- Collect data that captures both the individual (performance) and collective (success) characteristics of a proble;

- Carry out a quantitative and statistical analysis of the various performance and network measures;

- Measure the dynamic properties of the emergence of success and identify their driving forces;

- Work in teams to explore quantify success in a problem of their interest.

Assessment:

(1) Assessment type 1 (20% of the final grade). Synthesis of an area of success, chosen from a series of topics. Grade will be based on a presentation, as well as written summary.

(2) Assessment type 1 (20% of the final grade). Homework assignments.

(3) Assessment type 2 (10% of the final grade). Wikipedia Article on a topic freely chosen from the Science of Success literature. (20%)

(4) Assessment type 3 (50% of the final grade). A research project collecting data in some area of interest to the student, and analyzing the data using the tools discussed in the class.